AB0004 THE DISEASE GENOMIC GRAMMAR OF MYASTHENIA GRAVIS INDICATES A COMMON GENETIC BACKGROUND WITH RHEUMATOID ARTHRITIS
Authors: L. Papageorgiou, M. Zervou, R. Golfinopoulou, G. Bertsias, G. Goulielmos, E. Eliopoulos, D. Vlachakis
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Myasthenia Gravis (MG) is a rare, multifactorial autoimmune disease. It is caused by the presence of autoantibodies to the postsynaptic membrane of the neuromuscular junction causing impairment to neuromuscular transmission [1]. Various SNPs have been associated with MG with a number of genes possibly contributing to the disease pathogenesis [2]. Through the Disease's Genomic Grammar (DGG), as formulated by Bioinformatics tools, common genetic associated components have been established with RA, thus suggesting a genetic overlap in the manifestation of both diseases and possible concurrency in patients [3]. <h3>Objectives</h3> To create an ensemble of the genetic factors contributing to MG, to evaluate the most credible SNPs associated with disease manifestation, to establish a relationship with RA and to potentially assist in prognosis, prevention and personalized treatment of both diseases. <h3>Methods</h3> PubMed publications containing the term "myasthenia gravis" were analyzed with data mining and semantic techniques. Data Annotation enhanced the data collected, including SNPs obtained through GWAS, with information including variation type, alleles, relevance with phenotypes and additional clinical, genomic and functional information from databases including dbSNP, LitVar, ClinVar and Genes. Strong-Associated SNPs were further analyzed and validated. Genes related with both MG and RA were used to estimate a gene network with the use of the GeneMANIA tool and genetic and protein interactions, pathways and co-expression was studied. <h3>Results</h3> A candidate DGG was established containing a total 77 SNPs associated with MG and further categorized into three major classes. Within this database, different types of SNPs were identified with 27 SNPs representing Intron Variants (32.5%), 17 were 2KB Upstream/500B Downstream Variants (20.5%), 12 concerned Missense Variants (14.5%) and 7 SNPs were identified as 3' or 5' UTR Variants (8.4%). Class A included 40 Strong-Associated SNPs, related with 24 genes. MG and RA share 10 common Strong-Associated (Class A) SNPs (25%) related with 10 genes, based on the retrieved data. In a second level of analysis, these common genes create a functional network of a total of 29 genes and 855 total links, with 90.1% co-expression as generated by the GeneMANIA tool (Figure 1). <h3>Conclusion</h3> A higher frequency of concurrent autoimmune diseases is observed than the background prevalence and it has been demonstrated that MG coexists with other ADs in population studies [4,5]. Patients with concomitant MG and RA encounter more challenges in the therapeutic aspects of their health, considering that known disease-associated polymorphisms can be utilized in early diagnosis, prognosis and specialized treatment. Identifying the optimal genomic grammar in MG with the use of novel Bioinformatic tools may assist in the better understanding of this polygenic disease, while its association with RA and other ADs is a helpful step towards comprehending the shared biological pathways leading to autoimmunity. The data resulting from our study can be utilized towards the development of an application designed to assist clinical diagnosis by using the patients' genomic data, like the integrated bioinformatics tools Demetra for endometriosis [6] and Epione for SLE [7]. <h3>References</h3> [1]Golfinopoulou R. et al. Mol Med Rep, 2021. <b>24</b>(1):512 [2]Chia R. et al. Proc Natl Acad Sci U S A, 2022. <b>119</b>(5): e2108672119 [3]Papageorgiou L. et al. Annals Rheum Dis, 2022. <b>81</b>(Suppl 1):70 [4]Shi J. et al. Front Neurol, 2021. <b>12</b>:790941 [5]Mao Z.F. et al. Int J Neurosci, 2011. <b>121</b>(3):121 [6]Papageorgiou L. et al. Int J Mol Med, 2021. <b>47</b>(6):115 [7]Papageorgiou L. et al. Int J Mol Med, 2022. <b>49</b>(1):8 <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.